Shan Lu
Papers
1
Total Citations
2
H-Index
1
About
Dr. Shan Lu is a leading researcher in nonlinear control systems and robotics, with a focus on bridging robust control theory and safety-critical autonomy. Her most impactful work introduces the **Safe Sliding Mode Control (SSMC)** framework, which elegantly fuses sliding mode control (SMC) with control barrier functions (CBFs) via quadratic programming. This breakthrough enables nonlinear uncertain systems—such as mobile robots—to simultaneously achieve robust tracking performance and formal safety guarantees, a long-standing challenge in the field. By reformulating SMC's switching law as a constrained optimization problem, Dr. Lu’s approach ensures that robotic systems avoid obstacles and maintain stability even under model uncertainties and external disturbances. Her 2023 paper on SSMC for mobile robot path tracking has already garnered early citations, signaling its potential as a foundational method for safe autonomous navigation. Beyond this, her broader work explores the intersection of adaptive control, Lyapunov-based design, and real-time optimization, contributing to the next generation of resilient, safety-aware robotic systems. Dr. Lu’s research is particularly valuable for students and engineers working on autonomous vehicles, drone swarms, and industrial robotics, where the trade-off between aggressive performance and collision avoidance is critical.
Research Focus
Key Achievements
Top Papers
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